Operating method of intelligent vehicle driving control system

Abstract

In one aspect, an operating method of an intelligence vehicle driving control system is provided that comprises: a collecting step of collecting big data including a wheel torque and a speed for every vehicle type and traffic information; a torque calculating step of learning the big data using a predetermined machine learning model and inputs a specific desired speed profile to the machine learning model to calculate a motor torque of a driving vehicle; and an optimal speed profile deriving step of calculating an energy consumption required to generate the calculated motor torque using a predetermined dynamic programming method and a reverse vehicle dynamic model and deriving an optimal speed profile in which the energy consumption is minimized.

What is claimed is: 
     
         1 . An operating method of an intelligence vehicle driving control system, comprising:
 collecting big data including a wheel torque and a speed for vehicle type, and traffic information, by a communication unit;   learning the big data using a predetermined machine learning model and inputs a specific desired speed profile to the machine learning model to calculate a motor torque of a driving vehicle, by a control unit; and   calculating an energy consumption required to generate the motor torque using a predetermined dynamic programming method and a reverse vehicle dynamic model and deriving an optimal speed profile in which the energy consumption is reduced or minimized, by the control unit.   
     
     
         2 . The operating method of an intelligence vehicle driving control system according to  claim 1 , further comprising:
 controlling the driving vehicle according to the optimal speed profile, by the controller.   
     
     
         3 . The operating method of an intelligence vehicle driving control system according to  claim 1 , wherein calculating an energy consumption comprises:
 dividing a front section of the driving vehicle into at least two according to a speed condition for every section and deriving the optimal speed profile for each of at least two front sections.   
     
     
         4 . The operating method of an intelligence vehicle driving control system according to  claim 3 , wherein the calculating an energy consumption comprises:
 updating traffic information for the front section excluding a front section in which the vehicle travels, among two or more front sections.   
     
     
         5 . The operating method of an intelligence vehicle driving control system according to  claim 1 , wherein calculating an energy consumption comprises:
 normalizing speed values of all the vehicles which travel on the same path as the driving vehicle to calculate an average and a variance, determining a upper speed limit and a lower speed limit of the driving vehicle using the calculated average and the above-described variance, and deriving the optimal speed profile in consideration of the upper speed limit and the lower speed limit, by the control unit.   
     
     
         6 . The operating method of an intelligence vehicle driving control system according to  claim 5 , wherein in calculating an energy consumption, when the upper speed limit and the lower speed limit are determined, the control unit applies a weight to the variance by considering whether to drive in accordance with the flow of the surrounding vehicle or independently drive. 
     
     
         7 . The operating method of an intelligence vehicle driving control system according to  claim 1 , wherein in calculating an energy consumption, the controller considers an optimal speed according to a curvature of a road in which the driving vehicle travels as an optimal speed profile deriving condition. 
     
     
         8 . The operating method of an intelligence vehicle driving control system according to  claim 1 , wherein to calculate a motor torque of a driving vehicle comprises:
 learning a relationship of the wheel torque and the speed among the big data, by the machine learning model.   
     
     
         9 . The operating method of an intelligence vehicle driving control system according to  claim 8 , wherein to calculate a motor torque of a driving vehicle, the control unit inputs a desired speed profile to the machine learning model to calculate the motor torque. 
     
     
         10 . The operating method of an intelligence vehicle driving control system according to  claim 1 , wherein the machine learning model includes a convolutional neural network (CNN) and a recurrent neural network (RNN). 
     
     
         11 . The operating method of an intelligence vehicle driving control system according to  claim 8 , wherein the machine leaning model learns a rolling resistance, a gradient resistance, and an air resistance, among traffic information to be modeled. 
     
     
         12 . An operating system, comprising:
 a controller or communication unit configured to collect big data including a wheel torque and a speed for every vehicle type, and traffic information, by a communication unit;   a control unit configured to:   learn the big data using a predetermined machine learning model and inputs a specific desired speed profile to the machine learning model to calculate a motor torque of a driving vehicle; and   calculate an energy consumption required to generate the motor torque using a predetermined dynamic programming method and a reverse vehicle dynamic model and deriving an optimal speed profile in which the energy consumption is reduced or minimized.   
     
     
         13 . A vehicle configured to conduct a method of  claim 1 . 
     
     
         14 . A vehicle comprising a system of  claim 12 .